discoSNP runs in two steps: (1) detection of putative SNPs from the read datasets; (2) filtering and ranking based on coverage and base quality. Thanks to the use of the GATB-core library, the first step is able to handle very large datasets of billions of reads with a reasonable amount of memory. The processing of the mouse datasets required less than 6 GB of RAM. In comparison, the NIKS, KissSNP and Bubbleparse tools exceeded the memory limit on a server with 512 GB of RAM.
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